We are concerned by Data Driven Requirements Engineering, and in particular the consideration of user's reviews. These online reviews are a rich source of information for extracting new needs and improvement requests. In this work, we provide an automated analysis using CamemBERT, which is a state-of-the-art language model in French. We created a multi-label classification dataset of 6000 user reviews from three applications in the Health & Fitness field. The results are encouraging and suggest that it's possible to identify automatically the reviews concerning requests for new features. Dataset is available at: https://github.com/Jl-wei/APIA2022-French-user-reviews-classification-dataset.
@article{arxiv.2206.14669,
title = {Towards a Data-Driven Requirements Engineering Approach: Automatic Analysis of User Reviews},
author = {Jialiang Wei and Anne-Lise Courbis and Thomas Lambolais and Binbin Xu and Pierre Louis Bernard and Gérard Dray},
journal= {arXiv preprint arXiv:2206.14669},
year = {2022}
}
Comments
7th National Conference on Practical Applications of Artificial Intelligence, 2022. Saint-\'Etienne, France. article in English and French, 4 pages each